Forward Kinematics Analysis of Parallel Manipulator Using Dynamic Bacterial Foraging Optimization Algorithm Based on Clonal Selection

The forward kinematics analysis is the foundation for studying other performances of the parallel manipulator, which has been not very effect method to directly obtain high-precision solutions. Highly coupled non-linear motions of the parallel manipulator make the forward kinematics difficult to be solved. The forward kinematics can be transformed into an equivalent optimization problem by the property that it is easy to obtain the inverse kinematics. This paper proposes a dynamic bacterial foraging optimization algorithm based on clonal selection, which is called CDBFO, to directly obtain the globally optimal solution of the forward kinematics. A step strategy of piecewise dynamic adjustment and clonal selection are introduced into original bacterial foraging optimization algorithm and a comparison of benchmark functions tests show that CDBFO has the best performance among the other two algorithms. On this basis, this paper adopts CDBFO to solve the forward kinematics compared with the other two algorithms and the results show that CDBFO can not only obtain high accuracy of the forward kinematics, but also avoid complicated numerical derivation and sensitive problem of initial values. Absolute errors of the position and orientation are respectively less than 10e−04mm and 10e−04°, which has met the application requirement of the parallel manipulator on engineering precision.